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A forensic algorithm against median filtering based on coefficients of image blocks in frequency domain

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Abstract

Median filtering is a popular nonlinear denoising operator, it not only can be used for image enhancement, and it also is an effective tool in application of anti-forensics. So, the blind detection of median filtering is a particularly hot topic. Different from the existing median filtering forensic methods using the image pixel statistical features, this paper proposed a novel approach for detecting median filtering in digital images using coefficients of image blocks in frequency domain, based on the theory analysis and experiments test. Large numbers of experimental results show that the proposed approach achieved a high accuracy in median filtering detection and a good robustness of defending JPEG compression, the algorithm also can be used to locate the median filtering area. The approach achieves much better performance than the existing state-of-the-art methods with different format and size of image blocks, particularly when the image blocks are tiny and have high JPEG compression ratio.

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References

  1. Bayram S, Avcıbaş İ, Sankur B, Memon N (2006) Image manipulation detection. J Electron Imaging 15(4):041102–041102

    Article  Google Scholar 

  2. Cao G, Zhao Y, Ni R, Yu L, Tian H (2010) Forensic detection of median filtering in digital images. IEEE International Conference on Multimedia and Expo 26:89–94

    Google Scholar 

  3. Cao G, Zhao Y, Ni R, Kot AC (2011) Unsharp masking sharpening detection via overshoot artifacts analysis. IEEE Signal Process Lett 18(10):603–606

    Article  Google Scholar 

  4. Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol (TIST) 2(3):27

    Google Scholar 

  5. Chen C, Ni J, Huang R, Huang J (2012) Blind median filtering detection using statistics in difference domain. Lect Notes Comput Sci 7692:1–15

    Google Scholar 

  6. Image corpus of the 1st IEEE IFS-TC image forensics challenge [DB/OL]. http://ifc.recod.ic.unicamp.br/fc.website/index.py?sec=5

  7. Ker AD, Böhme R (2008, February) Revisiting weighted stego-image steganalysis. In: Electronic Imaging 2008. International Society for Optics and Photonics, pp 681905–681905

  8. Kirchner M, Bohme R (2008) Hiding traces of resampling in digital images. IEEE Trans Inf Forensics Secur 3(4):582–592

    Article  Google Scholar 

  9. Kirchner M, Fridrich J (2010) On detection of median filtering in digital images. Media Forensics and Security II 7541:754110–754112

    Article  Google Scholar 

  10. Kong X, Wang B, Yang M, Feng Y (2016) Multiple heterogeneous JPEG image hierarchical forensic. Advanced Multimedia and Ubiquitous Engineering. In: Lecture Notes in Electrical Engineering, Vol 393, pp. 509–516. Springer, Singapore

  11. Lin WS, Tjoa SK, Zhao HV, Liu KR (2009) Digital image source coder forensics via intrinsic fingerprints. IEEE Trans Inf Forensics Secur 4(3):460–475

    Article  Google Scholar 

  12. Liu A, Zhao Z, Zhang C, Su Y (2017) Median filtering forensics in digital images based on frequency-domain features. Multimedia Tools Appl 6:1–14

    Google Scholar 

  13. Luo W, Huang J, Qiu G (2010) Jpeg error analysis and its applications to digital image forensics. IEEE Trans Inf Forensics Secur 5(3):480–491

    Article  Google Scholar 

  14. Ng TT, Chang SF, Sun Q (2004) A data set of authentic and spliced image blocks. Columbia University, ADVENT Technical Report, p 203–2004

  15. Pevny T, Fridrich J (2008) Detection of double-compression in jpeg images for applications in steganography. IEEE Trans Inf Forensics Secur 3(2):247–258

    Article  Google Scholar 

  16. Popescu AC, Farid H (2005) Exposing digital forgeries by detecting traces of resampling. IEEE Trans Signal Process 53(2):758–767

    Article  MathSciNet  MATH  Google Scholar 

  17. Schaefer G, Stich M (2004) UCID: An uncompressed color image database. In: Storage & Retrieval Methods & Applications for Multimedia, pp 472–480

  18. Singh G, Singh K (2018) Forensics for partially double compressed doctored JPEG images. Multimed Tools Appl 77:485–502

    Article  Google Scholar 

  19. Stamm MC, Liu KJR (2010) Forensic detection of image manipulation using statistical intrinsic fingerprints. IEEE Trans Inf Forensics Secur 5(3):492–506

    Article  Google Scholar 

  20. Stamm MC, Liu KR (2011) Anti-forensics of digital image compression. IEEE Trans Inf Forensics Secur 6(3):1050–1065

    Article  Google Scholar 

  21. Swaminathan A, Wu M, Liu KJR (2008) Digital image forensics via intrinsic fingerprints. IEEE Trans Inf Forensics Secur 3(1):101–117

    Article  Google Scholar 

  22. Taimori A, Razzazi F, Behrad A, Ahmadi A, Babaie-Zadeh M (2017) A novel forensic image analysis tool for discovering double JPEG compression clues. Multimedia Tools Appl 76:7749–7783

    Article  Google Scholar 

  23. Yang J, Ren H, Zhu G, Huang J, Shi YQ (2017) Detecting median filtering via two-dimensional AR models of multiple filtered residuals. Multimedia Tools Appl 4:1–23

    Google Scholar 

  24. Yuan HD (2011) Blind forensics of median filtering in digital images. IEEE Trans Inf Forensics Secur 6(4):1335–1345

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. College of Software, Nankai University, Tianjin, 300350, China

    Dong-ping Wang & Tiegang Gao

  2. School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin, 300384, China

    Fusheng Yang

Authors
  1. Dong-ping Wang
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  2. Tiegang Gao
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  3. Fusheng Yang
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Correspondence to Dong-ping Wang.

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Wang, Dp., Gao, T. & Yang, F. A forensic algorithm against median filtering based on coefficients of image blocks in frequency domain. Multimed Tools Appl 77, 23411–23427 (2018). https://doi.org/10.1007/s11042-018-5651-z

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  • DOI: https://doi.org/10.1007/s11042-018-5651-z

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